4 papers
On Approaches to Building Surrogate ODE Models for Diffusion Bridges
Maria Khilchuk, Vladimir Latypov, Pavel Kleshchev +1
Diffusion and Schrödinger Bridge models have established state-of-the-art performance in generative modeling but are often hampered by significant computational costs and complex…
Differentiation methods as a systematic uncertainty source in equation discovery
Maria Khilchuk, Ilya Markov, Alexander Hvatov
In differential equation discovery algorithms, numerical differentiation is usually a fixed preliminary step. Current methods improve robustness with data subsampling and sparsity…
Towards Universal Neural Operators through Multiphysics Pretraining
Mikhail Masliaev, Dmitry Gusarov, Ilya Markov +1
Although neural operators are widely used in data-driven physical simulations, their training remains computationally expensive. Recent advances address this issue via downstream l…
Knowledge-aware equation discovery with automated background knowledge extraction
Elizaveta Ivanchik, Alexander Hvatov
In differential equation discovery algorithms, a priori expert knowledge is mainly used implicitly to constrain the form of the expected equation, making it impossible for the algo…